消費者交易型態與人格特質分析—以信用卡資料庫為例

Abstract

現在的金融服務業擁有龐大的顧客交易資料庫,行銷人員可以針對消費者的「動 態性」和「異質性」做一對一資料庫行銷。本研究嘗試利用問卷調查與資料庫結合 的方式,將四項人格特質:「內外控」、「自我監控」、「認知需求」與「金錢態 度」和 7 大類別的消費紀錄次數比及金額比進行邏輯斯迴歸分析,找尋其中的相關 性,並建立能用交易紀錄預測人格特質的模型。此模型能幫助企業依據每一個顧客 過去的購買行為模式,推測出其人格特質,並有效的篩選出適合目標客群的各項行 銷活動,使活動的總效益能達到最大,資源浪費降到最低,而能使顧客對公司的貢 獻達到最大化。

Nowadays, when it comes to marketing, the dynamic and heterogeneity of consumers need to be considered. Database analysis and market research have helped market analysts understand much more about consumer behavior, so enterprises can grasp the opportunities to drive their businesses. This thesis cross-analyzes 4 personalities and 7 categories of transaction records by collecting data from credit card questionnaires and a bank’s database. It aims to determine the connection between consumer personalities and consumer buying behaviors with a logistic regression model to predict customers’ personalities based on their transaction records. Thus, the model can assist enterprises in segmenting its customers with personalities and designing marketing activities for different target customer groups, which can increase the efficiency and effectiveness of the marketing resources.